Monsanto meets FDA requirements with SAS®

Researchers count on SAS® for data management and reporting

As soon as human communities began to settle in one place, cultivate crops and farm the land, they also began manipulating the genetic nature of the animals and crops they raised. For thousands of years, humans have crossbred crops to improve yields and animals to produce stronger, more productive offspring. When viewed from this perspective, the so-called modern fields of biotechnology and genetic engineering can certainly be classified as one of the earliest human activities.

Today, of course, biotechnology holds out promise for consumers seeking quality, safety and flavor in their food choices and for farmers seeking new methods to improve productivity and profitability. In fact, many public advocates support the use of biotechnology to stave off global hunger, assure environmental quality, preserve biodiversity, and promote health and food safety.

As a global provider of agricultural products and solutions, Monsanto is leading the charge to address these concerns. And in the continuing effort to champion agriculture productivity, the company depends on SAS to manage and analyze data for its many ongoing clinical studies and development projects.

SAS supports POSILAC^® studies
Richard Hintz, manager of the statistics group for Monsanto's Animal Agriculture division, says his team uses SAS on a daily basis for 99 percent of its data analysis needs. "We deal with preclinical research and registration trials, which include clinical trials, dose trials and toxicology trials," he says. "We use SAS for all of the statistical analysis that we send into the FDA as well as for our preclinical research."

In particular, Hintz and his team have spent many years supporting the development and registration efforts for POSILAC bovine somatotropin, a widely used pharmaceutical product that enhances dairy cow productivity.

Studied in preclinical trials since 1982 and approved by the U.S. Food and Drug Administration (FDA) in 1993, POSILAC has undergone the most extensive postapproval monitoring program ever conducted for any animal pharmaceutical product. As a result, POSILAC received unanimous support from the Veterinary Medicine Advisory Committee of the FDA in 1996. With this information-intensive product development Monsanto used and continues to use SAS to manage data quality, collection and analysis and to report the results.

"SAS automatically generates a lot of the information that we put into the FDA reports," explains Hintz. "We can submit all of our data to the FDA in SAS data sets along with the SAS program, and the agency can rerun anything that we've done to easily check or verify our work."

The FDA also requires annual stability reports and periodic adverse drug evaluation data for every pharmaceutical product on the market, and Monsanto uses SAS for these reporting needs as well.

SAS ensures data quality
Hintz uses SAS for data management and data quality checks as well. "We use SAS in a variety of ways before we even get to the analysis," he says. "We use it to manage some of the data that we receive electronically and for hand-recorded data as well, to verify whether the numbers have been entered correctly. Then we go through an additional verification, where we check the data against the protocol that shows what was supposed to be collected."

For example, if Hintz were to receive results of a pregnancy check for an animal that was never on a breeding list, SAS would automatically flag that entry as inconsistent and Hintz's team would know to go back through the data to investigate which entry was correct.

For some trials, Monsanto even places computers at the farms for data entry. That way, milk weights and other data can be entered into a database and SAS can distribute reports immediately to biologists who monitor the studies. Instant access to data helps Hintz and Monsanto's team of scientists detect and fix any unusual data quality issues as soon as they arise.

SAS eases information sharing
When it comes to SAS features, Hintz especially likes the automatic table generation and advanced output features of SAS. "SAS generates our tables electronically, so the accuracy of our tables is far better than it used to be," he says. In the past, data from SAS data sets had to be re-entered manually into the tables that were shared with Monsanto's scientists.

Now, the output delivery system in SAS makes it easy to provide data automatically to scientists or the FDA in any format requested. "With SAS, we can print the results in a different format quickly and generate graphs or charts straight from SAS. Or we can send the data in Excel or any other package that the scientists are familiar with, so they can do their own analyses."

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